Halogenated Species in RMG: Adding PFAS Chemistry, Exploring Halocarbon Blends, and Reducing Halocarbon Models with ML

Nora Khalil’s research focuses on improving the modeling of halogenated chemical systems—particularly PFAS and halocarbon refrigerants/suppressants—using computational tools and machine learning. She is enhancing the Reaction Mechanism Generator (RMG) to automatically model the thermal degradation of PFAS, a class of environmentally persistent and hazardous compounds, by incorporating accurate quantum chemistry data and developing PFAS-specific reaction…

Accelerating the investigation of cleaner fuels with automated kinetic model improvement 

Detailed kinetic models help us investigate alternative fuels for the next generation of cleaner combustion devices. While automated mechanism generators like Reaction Mechanism Generator (RMG) can build these models, the first results are usually not accurate enough to use without modification. We are developing a highly automated workflow that can iteratively improve these models without…